The western U.S. has millions of acres of forestlands at risk of large
and uncharacteristically severe wildfire. This is due to a variety of
factors, including decades of fire suppression as well as climate
change. Fuel treatments such as mechanical thinnings, prescribed burns,
and combinations of thinning and burning in fire-adapted forests can
reduce wildfire severity and potentially stabilize sequestered forest
carbon in coniferous, fire adapted forests of the western US; resulting
in avoided wildfire emissions (AWE) of greenhouse gases (GHG).
Accounting for GHG emission benefits of fuel treatments is challenging;
hence, scientific consensus and broad stakeholder buy-in from public
agencies, non-governmental organizations, and the private sector is key.
Using most recent forest vegetation and weather datasets as well as
forest growth and wildfire behavior models, we present an avoided
wildfire GHG emission accounting framework developed in collaboration
with key stakeholders in the western US as well as recent case studies.
This probability-based GHG emission accounting framework can not only
provide tools to quantify GHG benefits of fuel treatments, but can
specifically be employed to help fund fuel treatments through carbon
offset credits. The probability-based nature of this GHG emission
accounting approach has further application value for risk accounting to
forest carbon stocks from other stochastic events (e.g. drought, insect
outbreaks) as well as forest-based carbon offset protocols in general.